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. • Proficient computer skills, including competence in the use of MS Office and other software packages, especially word processing, database and spreadsheet skills. About Swinburne University of Technology
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. Selection Criteria Level A 1. A PhD in Remote Sensing, Plant phenotyping, Computer Vision, Machine Learning, or a related field. 2. Strong experience in image processing and computer vision, particularly
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You Completion or near completion of a PhD in the computer science or relevant field. Demonstrated experience with multi-modal imaging (RGB, thermal, spectral) and 3D data acquisition (e.g., LiDAR
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, the aim of this project is to develop and validate an experimental paradigm that can describe the dynamic processes underlying C2 agility and to characterise the situational factors by which C2 agility can
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on the fate of black holes in our Galaxy. Objectives To gain a full picture of the black hole population in our Galaxy, we aim to combine novel theoretical simulations of black holes with data from nascent
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skilled researcher who brings: A PhD in Computational Neuroscience, Physics, Engineering, Computer Science, Psychology, or a related discipline Strong quantitative and programming skills (preferably MATLAB
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Apply now Job no:531488 Work type:Full Time Location:Sydney, NSW Categories:Information Technology, Research Infrastructure One of Australia’s leading research & teaching universities Vibrant campus
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developing and implementing algorithms for processing, imaging or inversion of seismic data, preferably using MATLAB and/or Python. Experience or demonstrated ability in processing and analysis of surface
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University of Technology Swinburne’s strategy draws upon our understanding of future challenges. We choose to build Swinburne as the prototype of a new and different university – one that is truly
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vehicles capture videos or images for underwater pipes for inspection purposes. However, highly blurry or poor-quality videos can only be received under noisy environment. Therefore, developing accurate